Determining suitable ventilator settings for patients with alveolar hypoventilation during sleep

ABSTRACT

A method and apparatus for determining suitable settings for a servo-ventilator to be used during sleep. Respiratory characteristics of a patient are measured during an awake learning period. With these measured characteristics, a target ventilation setting may be calculated by alternative methods. The calculated setting may then be used for enforcing a minimum ventilation during a treatment period where ventilatory support is provided with a servo-controlled ventilator.

This application is a continuation of U.S. patent application Ser. No.10/683,239 filed Oct. 10, 2003, now U.S. Pat. No. 6,845,773 now allowedwhich is a continuation of Ser. No. 09/799,260, now U.S. Pat. No.6,644,312, which claims the Mar. 7, 2000 priority filing date of U.S.Provisional Application Ser. No. 60/187,565.

FIELD OF THE INVENTION

The present invention relates to the field of ventilatory assistance,and in particular, to methods and apparatus for determining suitableventilator settings in patients with alveolar hypoventilation duringsleep, and for delivery of those settings.

BACKGROUND OF THE INVENTION

Patients with sustained alveolar hypoventilation, such as patients withcentral alveolar hypoventilation syndrome (Ondine's curse), defectivechemoreflexes, obesity-hypoventilation syndrome, kyphoscoliosis, andneuromuscular disease, but also the large group of patients with chronicairflow limitation, can often breathe adequately while awake buthypoventilate during sleep, particularly during rapid eye movement (REM)sleep. Therefore, these patients require ventilatory assistance duringsleep. In addition, some may require oxygen therapy, particularly duringsleep.

However, from the clinical perspective, it is difficult to determine acorrect degree of ventilatory support to ensure adequate ventilationduring all sleep stages, particularly REM sleep, while avoidingexcessive ventilatory support in the awake state or in non-REM sleep.Excessive support can lead to over-ventilation with vocal cord closureand, ultimately, sleep disruption. Excessive support is alsouncomfortable to the awake patient. Equally difficult is selecting thecorrect amount of supplemental oxygen therapy. Patients need moresupplemental oxygen during periods of hypoventilation than during otherperiods, but excessive oxygen therapy can be deleterious or expensive.

A volume cycled ventilator set at a fixed respiratory rate and set todeliver a chosen amount of ventilation may largely solve theunder-ventilation problem. However, it introduces three new problems.

Firstly, it is necessary to experiment with various tidal volumesettings to find settings that achieve the desired level of blood gases.A rough estimate can be made from first principles, based on thepatient's weight, height, age, sex, etc. However, differences inmetabolic rate, in particular, the gas exchanging efficiency of thelungs, can introduce very large errors. In current practice, expertclinical experience is required to make such an assessment, and usuallythe chosen target ventilation needs to be tested overnight anditeratively refined.

Secondly, such ventilators when correctly set are uncomfortable for mostpatients because the patient can only breathe at exactly the rate anddepth set by the machine.

Thirdly, the ventilator may not be set accurately. If the ventilator isset to give slightly too much ventilation, the subject will beover-ventilated, leading to airway closure and very high airwaypressures. Alternatively, if the ventilator is set to give slightly toolittle ventilation, the subject will feel air hunger.

The usual clinical compromise solution is to use a bilevel ventilatorset to administer a fixed higher airway pressure during inspiration andanother fixed lower airway pressure during expiration. The device istypically set to trigger from the expiratory pressure to the inspiratorypressure on detection of patient inspiratory airflow and to trigger backto the expiratory pressure on cessation of patient inspiratory airflow.A backup rate is provided for the case where the patient makes no effortwithin a given period.

This solution is a compromise for several reasons. Firstly, it isdifficult to select a degree of assistance that will adequately supportthe patient during, for example, REM sleep, without over-ventilating thepatient during non-REM sleep or while the patient is awake. We have mademeasurements of the degree of support that makes typical patients feelmost comfortable during the daytime and found it to be much less thanthe degree of support that provides adequate ventilation during sleep.In many patients, the degree of support required during sleep, whendelivered to the patient in the awake state, actually feels worse thanno support at all. Secondly, the square pressure waveform isuncomfortable and intrusive in patients with normal lung function.Thirdly, it is necessary to empirically set the device while the patientsleeps, and it may take several iterations to find an adequatecompromise. This procedure requires highly experienced staff and is veryexpensive.

One method of providing more comfortable ventilatory support isproportional assist ventilation. A device using this method seeks toprovide a more comfortable pressure waveform that necessarily avoidsover-ventilation because the patient must supply some effort, which isthen amplified by the device. Unfortunately, this method will not workin the case of patients with absent or severely impaired chemoreflexesin sleep. This problem exists in people with Ondine's curse or obesityhypoventilation syndrome, or in people in whom the coupling betweeneffort and result reduces dramatically during sleep, for example,patients with neuromuscular disease, where accessory muscle activity iscompletely lost during sleep. This problem also occurs in a very widerange of patients during REM sleep when there is routinely abnormalchemoreflex control, even in normal subjects.

The broad class of servo ventilators partially address the problem ofthe patient requiring much less support while awake than asleep. Thephysician specifies a target minute ventilation, and the device suppliessufficient support to deliver the specified minute ventilation onaverage. While the patient is awake and making large spontaneousefforts, the device will provide zero support. However, it will providesupport as required during sleep. Further refinements of theservo-ventilator including the features of a smooth pressure waveformtemplate, resistive unloading, low source impedance so that the patientcan breathe more than the target ventilation if desired, and a minimumdegree of support chosen to be comfortable in the awake state are taughtin commonly owned International Publication No. WO 98/12965.

The above approaches all require the specification of a targetventilation, and either a respiratory rate or a backup respiratory rate.In addition, in patients requiring added supplemental oxygen, it isnecessary to also specify the amount of added oxygen. Finally, using theabove approaches, if the device is incorrectly calibrated, it willdeliver a different minute ventilation than the one chosen.

BRIEF DESCRIPTION OF THE INVENTION

It is an objective of the present invention to permit the determinationof suitable ventilator settings and supplemental oxygen flow rate, foruse with a servo ventilator, by measurements and observations made onthe subject during the daytime.

It is a further objective to permit the delivery of the chosen settingseven in the case of incorrect calibration of the ventilator.

Further objectives, features and advantages of the invention will becomeapparent upon consideration of the following detailed description.

In its broadest sense, the present invention involves a method andapparatus for determining ventilator settings such as a desired targetventilation and/or respiratory rate. During a learning period, while apatient is preferably in a relaxed and awake state, respiratory orventilation characteristics including, minute ventilation, andoptionally blood gas saturation, such as arterial hemoglobin oxygensaturation, and respiratory rate, are measured by a ventilator. Themeasurements are then used to determine ventilator settings for useduring the patient's sleep. In a preferred form, the deviceautomatically calculates the desired target ventilation and respiratoryrate during or at the end of the learning period, and saves and laterapplies these settings during subsequent therapy.

In one embodiment, the ventilation target is calculated as a fixedpercentage of an average ventilation taken over the entire learningperiod. Alternatively, the ventilation target may be a fixed percentageof an average ventilation taken over a latter portion of the learningperiod to eliminate ventilation measurements from non-relaxed breathingefforts from an initial portion of the learning period. In a stillfurther alternative, the ventilation target is determined from a graphof spontaneous ventilation and oxygen saturation measurements madeduring the learning period. In this method, the target ventilation istaken as a fixed fraction of the ventilation that on average achieves adesired arterial oxygen saturation level.

DESCRIPTION OF THE DRAWINGS

FIG. 1 shows a flow chart for an embodiment of a simple form of theinvention;

FIG. 2 shows a flow chart for an embodiment of a more elaborate form ofthe invention;

FIG. 3 shows a graph of saturation vs. ventilation with a fittedexponential curve and calculated target ventilation;

FIG. 4 depicts an illustrative apparatus for implementing the method ofthe invention; and

FIG. 5 depicts a smooth and comfortable ventilator waveform templatefunction Π(Φ) which when multiplied by an amplitude specifies onecomponent of the mask pressure as a function of phase.

DETAILED DESCRIPTION OF THE INVENTION

Referring to FIG. 1, a method embodying the present invention generallyinvolves a learning period 2 and a treatment period 4. During thelearning period 2, a ventilator setting, such as a target ventilationV_(TGT), is determined (step 8). This determination is based uponrespiratory characteristics of the patient, for example, a measure ofventilation, taken while a patient is awake (step 6). The targetventilation is then used during the subsequent treatment period 4 whilethe patient sleeps. In a typical application, the learning period 2 isin the daytime, with the patient awake, and the treatment period 4 is atnight, with the patient asleep. However, more generally, the learningperiod 2 is any period where the patient is quietly awake, and thetreatment period 4 (or in general, periods) may also be any time of dayor night, with the patient either awake or asleep in any combination.

For example, consider a learning period 2 in which a patient is quietlyrelaxed and awake. The patient is for preference distracted frombreathing, for example, by watching television but remaining still andquiet. Typically, the learning period will be of the order of one hour'sduration or longer, although shorter periods are practical. During thelearning period 2, the subject breathes via a nosemask, facemask, orother suitable interface, as chosen for use during sleep, from aservo-ventilator such as the apparatus of FIG. 4. During this learningperiod 2, the servo-control of ventilation is disabled, and the deviceis set to deliver a fixed minimum degree of support (pressure modulationamplitude) A_(MIN), typically 6 cm H₂O, chosen to make the patient feelcomfortable.

During this learning period, ventilation is measured (step 6).Optionally, as shown in FIG. 2, oxygen saturation levels may be measured(step 16) by an oximeter. A target ventilation for use during sleep isselected or determined (step 8) based on the ventilation measurementsand optionally oxygen saturation measurements. Thus, a targetventilation may be, for example, set to be just under the known adequatemeasure of ventilation. If, during the learning period, the patient werecompletely relaxed and awake throughout the period, and unaware ofbreathing, then ventilation would settle to a value demonstrablyadequate in the awake state, or at least substantially better thanduring untreated sleep, and therefore adequate for treatment duringsleep.

Switching from a learning period 2 to a treatment period 4, the targetventilation is used by the ventilator to deliver ventilation. Theventilator will measure the patient's ventilation during sleep in step10. The ventilator will then derive a pressure amplitude to maintaindelivered ventilation to at least equal the target ventilation in step12. Mask pressure is then calculated and delivered to the patient, instep 14, as a function of the pressure amplitude. The ventilator willthen maintain actual ventilation to at least equal the targetventilation. Optionally, a target respiratory rate may also be set to avalue determined during the learning period. For preference, this is theaverage respiratory rate during the last 75% of the learning period.

The first advantage of this method is that the target ventilation (andoptionally the respiratory rate) is now demonstrably known to besuitable for the particular patient. The second advantage is that anyerrors in measurement of ventilation by the device will be cancelledout, and the device will guarantee at least the chosen fraction of thepatient's spontaneous awake ventilation.

In one embodiment of the invention, the target ventilation is a targetminute ventilation taken as a fixed percentage of the average minuteventilation during the entire learning period. Typically this percentagewill be 90%, to allow for the fact that metabolic rate decreasesslightly during sleep. In a preferred embodiment, the above calculationis made by the device itself. The principle underlying this method isthat the subject has on average relatively normal arterial partialpressure of carbon dioxide while awake, the principal abnormality ofventilation being confined to sleep. Since the relationship betweenminute ventilation and arterial carbon dioxide is approximately linearover small departures from the mean, the average ventilation awake willensure the average partial pressure of carbon dioxide awake.

Many subjects do indeed have elevated carbon dioxide tension in thedaytime as well as at night, but if the nocturnal rise is prevented,then the subject will gradually over days reset his or her respiratorycontroller to a more normal set-point. It would then be appropriate torepeat the daytime learning procedure and determine a new targetventilation after about one to two weeks of therapy, to take advantageof this resetting.

It would in principle be possible to calculate a final targetventilation for use during the treatment period from a measure of thesubject's awake daytime arterial partial pressure of carbon dioxide, thedesired final awake daytime partial pressure of carbon dioxide, and thecurrent target ventilation from a prior learning period. A simplecalculation, ignoring changing dead space to tidal volume ratio is:Final target ventilation=current target ventilation times current awakearterial partial pressure of carbon dioxide divided by final desiredawake arterial partial pressure of carbon dioxide. However, applyingthis final target ventilation immediately within the treatment periodwould lead to akalosis and vocal cord closure during sleep. This willdisturb the effectiveness of therapy by inducing upper airwayobstruction.

In a second and preferred embodiment, the first portion of the learningperiod, typically 20 minutes, is discarded because the patient istypically particularly aware of his or her ventilation as a result ofcommencing ventilatory therapy. Thus, the measurements from steps 6 and16 are recorded only during a second portion, preferably lasting 40minutes or more.

A third embodiment is useful in the case where the subject's breathingchanges slowly with time by a large amount during the learning period,for example, if the subject is initially very anxious, later breathesnormally, and finally falls asleep and desaturates. To address thissituation, measurements of oxygen saturation are taken with an oximeteralong with measurements of spontaneous ventilation. At the end of thelearning period, a graph of oxygen saturation versus spontaneousventilation is drawn. Then, using this graph, the target minuteventilation is taken as a fixed fraction (typically 90%) of theventilation that on average achieves a desired arterial oxygensaturation.

The basis for this method is that some subjects, for example, those withobesity hypoventilation syndrome, fall asleep easily for short periodsduring the learning period. During these short periods, the subjectswill reduce their ventilation and desaturate. Thus, it is intended thatthe method use only data from periods where the awake saturation isadequate.

Conversely, other patients, particularly early in the learning period,are anxious and over-ventilate. Periods where the ventilation is veryhigh but the saturation has not importantly increased should thereforealso be ignored. Because the subjects are awake during the learningperiod, they will tend to fidget and move about, which causes oximeterartifact. Therefore, the subjects should be made very comfortable andasked to relax and remain quiet and still as far as possible.

Preferably, the oximeter is a pulse oximeter with excellent movementartifact immunity, such as the device produced by the MasimoCorporation. However, due to patient circulation times and processingtimes in the oximeter, changes in saturation lag changes in ventilationby typically 20–30 seconds. Furthermore, due to the oxygen storagecapacity of the lungs and blood, very short changes in ventilation(typically less than 10–40 seconds) produce little or no change insaturation. Therefore, the ventilation measurements should be delayed bythe expected circulation time plus oximeter processing time (e.g., 20–30seconds), and low-pass filtered to compensate for the low-pass filteringof the saturation by the body oxygen storage capacity (e.g., with a timeconstant of 10–40 seconds) in order to better relate changes insaturation to changes in ventilation.

This selection of a suitable delay and time constant can be doneautomatically, for example, by using the method of least squaresnonlinear regression to search the expected range of delay and timeconstants to find the combination that minimizes the scatter around thesaturation vs. ventilation graph. For example, the least squaresprocedure can fit an exponential curve to the saturation vs. ventilationgraph, such asS=S _(max)(1−e ^(−kv))

where S is the saturation, v is the ventilation, and S_(max) and k arefitted constants. However, there is no particular physical significancein the use of the exponential curve. The actual shape of the saturationvs. ventilation graph is very complex, and an exponential curve is justone of a large number of curves that could be fitted. One such fittedcurve 18 is represented in the graph of FIG. 3.

Typically, the desired arterial oxygen saturation will be in the range90–95%, for example 92%, because a goal of ventilatory support is tokeep the saturation above 90%, but 95% is normal during sleep. Thedesired level of arterial oxygen saturation can be chosen by theclinician with reference to the patient's clinical condition.Thereafter, in a preferred form, the target ventilation can becalculated automatically from the above fitted exponential equation.Alternatively, the desired oxygen saturation can be chosen by inspectionof the oxygen saturation vs. ventilation graph. In general, the graphwill include a quasi-plateau portion at high ventilations, where furtherincreases in ventilation yield little further increase in saturation butrisk over-ventilation and hypocapnia, and a steep portion at lowventilations, where the risk is of hypoxia and hypercapnia. A suitabledesired saturation is two percent below the plateau saturation. Forexample, in a subject with normal lungs, the plateau will commence at97%, and even doubling the ventilation will not increase saturationabove 98%. Therefore, a suitable desired saturation would be 95%. Insubjects with lung disease, the plateau will begin at a lower saturationthan in normal subjects. In a preferred embodiment, the desiredsaturation is calculated automatically as, for example, 2% less than theconstant S_(max). This is illustrated in FIG. 3.

However, this least squares nonlinear regression method is not useful inthe case where there are negligible slow changes in saturation becauseit will not be possible to fit an exponential to the saturation vs.ventilation graph. If the standard deviation of the saturation residualsabout the fitted curve is not less than approximately 50% of thestandard deviation about a simple average saturation, then the targetventilation should be calculated as in the second embodiment (forexample, 90% of the mean ventilation during all but the first 15 minutesof the learning period).

The above procedures will yield at least a good first estimate ofventilator settings, without having to adjust the ventilator settingsduring the night. However, a potential problem with the embodimentsdescribed above is that the subject might stably over-ventilate orunder-ventilate for the entire period of the learning session.Therefore, in some subjects, it may be desirable to confirm that thetarget ventilation is satisfactory by measuring arterial or arterializedcapillary carbon dioxide concentration in the morning followingovernight therapy, and increasing the target ventilation if the morningarterial carbon dioxide concentration is too high, or decreasing thetarget ventilation if the morning arterial carbon dioxide concentrationis too low. Another approach to guard against the effects of sustainedover or under-ventilation during the learning period is to measurearterial blood gases, particularly arterial PCO ₂, pH, and bicarbonateat the end of the learning session. In stable subjects, the pH will bein the normal range, and in subjects who over-ventilated orunder-ventilated, the pH will be altered. Standard nomograms areavailable which would permit one to calculate the PCO ₂ that the subjectwould have had if they were breathing steadily. The target ventilationshould then be multiplied by the ratio of the observed PCO ₂ to theestimated stable PCO ₂.

The target ventilation calculated using any of the above procedures isbased on the assumption that the ventilation that is adequate in thedaytime, i.e., while the patient is awake, will also be adequate atnight, i.e., while the patient is sleeping, if allowance is made for areduction in metabolic rate. As previously mentioned, clinical methodsof calculating a target ventilation also attempt to allow for variationsin metabolic rate, for example, by using age, height, weight, sex,skinfold thickness, etc., and gas exchange efficiency (chiefly deadspace to tidal volume ratio, but also V/Q distribution,arterial-alveolar oxygen tension gradient, diffusing capacity,spirometry, clinical experience, and so forth). The present method is inprinciple more robust than these methods because it very directlymeasures the patient's actual ventilatory need. Nevertheless, it ispossible to produce a final target ventilation which is a weightedaverage of the present method and any combination of other methods. Forexample, patient estimation information such as age, height, weight,sex, alveolar dead space, etc., may be used with any other knownestimation method to calculate an estimated target ventilation using theother known method. Then a final target ventilation may be determined,which is a weighted average of the present method and the other knownestimation method. Alternatively, the target ventilation calculated froman awake learning period may be used as one input variable to an expertsystem, for example, a fuzzy expert system, in which other inputvariables include one or more of age, height, weight, sex, severity andkind of disease, spirometry, blood gases, alveolar dead space and otherlung function results.

Several of the above methods calculate a mean ventilation over a periodof time. If the measurement of ventilation (as opposed to the subject'sactual true ventilation) is noisy, it may be advantageous to calculate amore robust measure of central tendency, such as a trimmed mean or amedian. Similar comments apply to other quantities measured, such asrespiratory rate and arterial oxygen saturation measured by pulseoximetry.

Some patients require the addition of supplemental oxygen in order tomaintain adequate oxygenation and saturation, even if minute ventilationis adequate. This is due to ventilation-perfusion mismatch. In suchpatients, the learning period may be repeated at one or more differentlevels of inspired oxygen, e.g., 21%, 24%, and 28%, or at one or moredifferent levels of added oxygen, e.g., 0, 2, and 4 L/min. This willyield three different target ventilations, at three correspondingsaturation levels. The physician may then choose one particularsupplemental oxygen level, and the corresponding target ventilation. Ingeneral, this will be the lowest added oxygen level that permits asatisfactory saturation at a practicable target ventilation. If theventilator is then set to deliver the target ventilation with theselected level of supplemental oxygen therapy, then the subject willstill be guaranteed adequate ventilation, and the saturation will alsobe adequate, providing the ventilation-perfusion mismatch does notworsen significantly during sleep.

A suitable apparatus for implementing these methods is shown in FIG. 4.The apparatus is described in more detail in commonly ownedInternational Publication No. WO 98/12965 entitled “Assisted Ventilationto Match Patient Respiratory Need.” (U.S. patent application Ser. No.08/935,785, filed on Sep. 23, 1997). The foregoing application is herebyincorporated by reference. Generally, the apparatus provides breathablegas at controllable positive pressure to a patient's airway. Referringto FIG. 4, a blower 20 supplies breathable gas to a mask 21 incommunication with a patient's airway via a delivery tube 22 andexhausted via an exhaust 23. Airflow at the mask 21 is measured using apneumotachograph 24 and a differential pressure transducer 25. The maskflow signal f(t) from the transducer 25 is then sampled by amicroprocessor 26. Mask pressure is measured at the port 27 using apressure transducer 28. The pressure signal from the transducer 28 isthen sampled by the microprocessor 26. The microprocessor 26 sends aninstantaneous mask pressure request (i.e., desired mask pressure) signalP(t) to a servo-controller 29, which compares the pressure requestsignal with the actual pressure signal from the transducer 28 to controla fan motor 30. Microprocessor settings can be adjusted via a serialport (not shown).

It is to be understood that the mask could equally be replaced with atracheotomy tube, endotracheal tube, nasal pillows, or other means ofmaking a sealed connection between the air delivery means and thepatient's airway. Moreover, as an alternative to the blower 20, theventilator may use any source of breathable gas including air/oxygenmixtures at controllable pressure.

The microprocessor 26 accepts the mask airflow and pressure signals, andfrom these signals determines the instantaneous flow through any leakbetween the mask and patient, by any convenient method. For example, theconductance of the leak may be estimated as the instantaneous maskairflow, low-pass filtered with a time constant of 10 seconds, dividedby the similarly low-pass filtered square root of the instantaneous maskpressure, and the instantaneous leakage flow may then be calculated asthe conductance multiplied by the square root of the instantaneous maskpressure. Respiratory airflow is then calculated as the instantaneousmask airflow minus the instantaneous leakage flow.

The desired mask pressure is described by the following equation:P=P ₀ +Rf+AΠ(Φ)where:

P₀ is a desired end expiratory pressure chosen to splint the upper andlower airways or alveoli, or to reduce cardiac preload or afterload, forexample, 5 cm H₂O;

R may be zero, but is preferably any value less than the patient'sactual airway resistance;

f is respiratory airflow, measured, for example, using apneumotachograph in the mask, and correcting for leak, for example, asdescribed in the commonly owned International Publication referred toabove;

Φ is the phase in the patient's respiratory cycle; taken as varyingbetween zero and 1 revolution, with zero corresponding to start ofinspiration and 0.5 corresponding to start of expiration, preferrablycalculated using fuzzy logic;

Π(Φ) is a pressure waveform template, initially set to be similar tothat shown in FIG. 5, for example, comprising a raised cosine followedby an exponential decay (unlike a true exponential decay, the waveformof FIG. 5 falls exactly to zero by the end of expiration, so that thereis no step change at the start of the next breath); and

A is a pressure modulation amplitude, for example, using clippedintegral control as follows:A=−G∫(0.5|f|−V _(TGT))dt,

where G is a servo gain (for example, 0.3 cm H₂O per L/min per second),V_(TGT) is a desired target ventilation (e.g., 7.5 L/min), and theintegral is clipped to lie between A_(MIN) and A_(MAX) (for example, 3and 20 cm H₂O) chosen for comfort and safety.

To implement the learning period methods using this apparatus, themicroprocessor 26 may be programmed to implement a “learn” mode and a“treat” mode. During the “learn” mode, the pressure modulation amplitudeA is set to a very low value, chosen to be enough to make the patientfeel comfortable while awake, but not enough to do all the work ofbreathing. In all subjects, an amplitude of 3 cmH₂O will besatisfactory. However, the exact value is non-critical. In some subjectswith very high work of breathing, larger values can be used if desired.During this learn mode, the microprocessor 26 may store ventilationdata, for example, in SRAM or EEPROM, for use in calculation of thetarget ventilation V_(TGT). Optionally, the microprocessor 16 may alsostore arterial hemoglobin oxygen saturation data from a pulse oximeter32, or other similar device for this calculation. At the conclusion ofthis mode, the microprocessor 26 automatically calculates the targetventilation and automatically stores this target ventilation forsubsequent use. During subsequent therapy, with the device in the“treat” mode, the pressure modulation amplitude is automaticallyadjusted in order to servo-control ventilation to equal or exceed thetarget ventilation determined in the “learn” mode.

While this embodiment of the invention incorporates both the learn andtreat modes into a single apparatus, various simplifications arepossible. For example, the device used to measure ventilation during thelearning period may be different from the device used to subsequentlytreat the patient. In this case, the target ventilation can becalculated manually or by using analog electronics and the targetventilation can be stored and/or transferred manually to anotherventilator to be used during the treatment period.

It is desirable that the device should not accidentally be delivered tothe patient for unattended use unless it is certain that the device isin the “treat” mode, using settings that have been correctly determinedeither in the “learn” mode or as prescribed manually by a physician.Therefore, in a preferred form, a device embodying the invention hasthree modes, the “learn” and “treat” modes described in detail above,plus an inoperative mode in which the device will not operate. Thedefault state as delivered is the inoperative mode. It may be placed inany of the three modes by the physician, for example, by sendingcommands to the microprocessor via a serial port. However, if it isinadvertently left in the “learn” mode, it will automatically revert tothe “inoperative” mode on power-up.

In a preferred form, the device can be programmed to remain in “learn”mode for a specified period of time, such as 1 hour, and at the expiryof said time, the microprocessor will notify the physician, for example,via a serial port or other input/output device, of the settingsdetermined during the learning period using any of the automatic methodsdescribed above. The physician will then be prompted to accept or editthese settings, and after acceptance or editing, the device willautomatically switch to the “treat” mode at these accepted or editedsettings.

For several of the disclosed methods, the ventilation quantity measuredis minute ventilation and the calculated target ventilation is intendedfor use with a servo-ventilator with fuzzy phase detection and resistiveunloading as described and illustrated in FIG. 4. However, the generalmethod is equally applicable to a simple servo ventilator. Furthermore,if the ventilation quantity measured is tidal volume, and the calculatedquantity is a target tidal volume, the controlled device can be a volumecycled ventilator.

An embodiment of the invention using the apparatus of FIG. 4 was testedin nine subjects with a wide variety of respiratory disorders, includingkyphoscoliosis, neuromuscular disease, obesity-hypoventilation syndrome,and chronic airflow limitation. In this embodiment, the respiratorytherapist estimated the target ventilation by eye from a graph ofsaturation vs. ventilation. In every case, as assessed usingpolysomnography, overnight oximetry, transcutaneous PCO₂, and morningblood gases, the subjects slept and breathed either as well as, orbetter than, they did on another night in which they were treated usingstandard bi-level therapy manually titrated by an expert respiratorytherapist skilled in the art. The target ventilation was also calculatedas 90% of the mean ventilation during the latter 40 minutes of eachlearning period. There was a 97% correlation between the targetventilation automatically calculated from the minute ventilation only,and the target ventilation estimated by-eye from the saturation vs.ventilation graphs, demonstrating that in most subjects, it is notnecessary to measure saturation.

Although the invention has been described with reference to particularembodiments, it is to be understood that these embodiments are merelyillustrative of the application of the principles of the invention.Numerous modifications may be made in the illustrative embodiments ofthe invention and other arrangements may be devised without departingfrom the spirit and scope of the invention.

1. A method for determining at least one setting of a ventilator to beused during sleep comprising the steps of: measuring at least onerespiratory characteristic of a patient during a learning period whilethe patient is awake; and determining at least one setting value fromsaid at least one respiratory characteristic to be used for theoperation of said ventilator during a subsequent treatment period ofsleep.
 2. The method of claim 1 wherein said at least one respiratorycharacteristic is a measure of ventilation.
 3. The method of claim 2wherein at least one setting value is a target ventilation.
 4. Themethod of claim 3 wherein said target minute ventilation is a functionof said measure of ventilation.
 5. The method of claim 4 wherein saidfunction is a fixed proportion.
 6. The method of claim 5 wherein saidfixed proportion is about 90%.
 7. The method of claim 2 wherein anothersaid respiratory characteristics is arterial hemoglobin oxygensaturation.
 8. The method of claim 7 wherein at least one setting valueis calculated from the relationship between said oxygen saturation andsaid measure of ventilation.
 9. The method of claim 2 wherein at leastone setting value is derived through a fuzzy expert system with inputvariables including a target ventilation derived from said measure ofventilation and patient estimation information.
 10. The method of claim9 further comprising the step of analyzing patient estimationinformation to determine an estimated target ventilation, wherein saidsetting value is a calculated weighted average of said estimated targetventilation and a second target ventilation derived from said measure ofventilation.
 11. The method of claim 3 wherein said step of measuring atleast one respiratory characteristic includes deriving measures ofspontaneous ventilation and measures of arterial oxygen saturation. 12.The method of claim 11 wherein said step of determining a setting valueincludes an analysis of a graph of said measures of spontaneousventilation and measures of arterial oxygen saturation.
 13. The methodof claim 12 wherein said graph includes a fitted curve derived from saidmeasures of spontaneous ventilation and measures of arterial oxygensaturation using least squares nonlinear regression.
 14. The method ofclaim 13 wherein said curve is an exponential function.
 15. The methodof claim 13 wherein said measures of spontaneous ventilation are delayedand low-pass filtered to associate changes in said arterial oxygensaturation with changes in said measures of spontaneous ventilation. 16.The method of claim 1 wherein said at least one respiratorycharacteristic is a measure of respiration rate.
 17. The method of claim16 wherein at least one setting value is a target respiration rate. 18.The method of claim 17 wherein said measure of respiration rate is anaverage respiration rate.
 19. The method of claim 1 wherein said atleast one respiratory characteristic is a measure of arterial partialpressure of carbon dioxide.
 20. The method of claim 1 wherein at leastone setting value is a target ventilation which is a product of acurrent target ventilation and the measure of arterial partial pressureof carbon dioxide divided by a desired arterial partial pressure ofcarbon dioxide.